Recently, there has been an increased interest in the exploitation of background knowledge in the context of text mining tasks, especially text classification. At the same time, kernel-based learning algorithms like Support Vector Machines have become a dominant paradigm in the text mining community. Amongst other reasons, this is also due to their capability to achieve more accurate learning r...

A proof is given of several conjectures from a recent paper Nakaya concerning the supersingular polynomial [Formula: see text] for Fricke group text], text]. One these gives formula square (mod text]) in terms certain resultant, and other relates primes which splits into linear factors to orders sporadic simple groups.

encryption is an important tool for managing and protecting information. cryptography is the only practical means of sending information over an insecure channel. these channels may be computers, telephone lines, satellite, etc. the increasing use of electronic means of data transfer from one point to another, coupled with the growth in networking and internet communication, has extended the ne...

We propose a cascaded linear model for joint Chinese word segmentation and partof-speech tagging. With a character-based perceptron as the core, combined with realvalued features such as language models, the cascaded model is able to efficiently utilize knowledge sources that are inconvenient to incorporate into the perceptron directly. Experiments show that the cascaded model achieves improved...

In this article, we developed a Bayesian model to characterize text line and text block structures on document images using the text word bounding boxes. We posed the extraction problem as finding the text lines and text blocks that maximize the Bayesian probability of the text lines and text blocks given the text word bounding boxes. In particular, we derived the so-called probabilistic linear...

We show for both English POS tagging and Chinese word segmentation that with proper representation, large number of deterministic constraints can be learned from training examples, and these are useful in constraining probabilistic inference. For tagging, learned constraints are directly used to constrain Viterbi decoding. For segmentation, character-based tagging constraints can be learned wit...

The concept of text coherence was developed for linear text, i.e. text of sequentially organized content. The present article addresses to what extent this concept can be applied to hypertext. Following the introduction (section 1), I will define different aspects of text coherence (section 2). I will then explain the importance of the sequential order of text constituents for coherence-buildin...

A new almost linear time algorithm for indexed full-text search is presented. The algorithm uses a modified factor oracle as an index database. A factor oracle is an acyclic automaton made from an input text, and it recognizes all of substrings in the text. It can be built in time proportional to the text length, and it is more space economical and easy to implement comparing similar machinerie...

Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are just a few problems. Text detection can be specially suited for georeferencing business, navigation, tourist assistance, or to help visual impaired people. In this paper, we propose a general methodology to deal with the probl...